"Network Emergence: How Small Worlds Make a Big Difference in the Broadway Musical Industry, 1877 to 1995", Brian Uzzi, February 14, 2003

Strategy seminar, University of Toronto Rotman School, Friday, February 14, 2003, 1:00 pm

These participant's notes were created in real-time during the meeting, based on the speaker's presentation(s) and comments from the audience. These should not be viewed as official transcripts of the meeting, but only as an interpretation by a single individual. Lapses, grammatical errors, and typing mistakes may not have been corrected. Questions about content should be directed to the originator. These notes have been contributed by David Ing (daviding@systemicbusiness.org) at the IBM Advanced Business Institute ( http://www.ibm.com/abi ).

Welcome by Kim Bates, Rotman School

Brian Uzzi, Northwestern University

New work on the small world problem

Small worlds feature a network both highly clustered, but with short pathways

What accounts for the process in which small worlds form?

Do small worlds actually make a difference?

Some research in the Broadway musical industry

Foreshadow:

What leads to these questions?

The small world idea from the study by Stanley Milgrom, 1967

1970, Granovetter is in the same department as Milgrom in Harvard

1977, Ron Burt builds on Granovetter with structural holes

1997, Duncan Watts

Two questions:

Two methods:

Finidings:

Building on Watts and Milgrom

What do we find, in the Broadway music industry?

Data sources:

[Question about broader networks in other theatre centers?]

[Comment:  Broadway becomes a provider to other theatre centres:  touring companies?]

1878 to 1995 [graphs]

Time frame:

In 1893, year 16

In 1894, year 17

In 1895, year 18:

In 1896, 135 continuing with 29 new

In 1897, develops a real small world, with clustering and short paths

In 1898

In a series

[Question:  Does the network ever become fully connected?]

Emergence:  braids turning into a ring happens very quickly.

The reason a small world obtains, is the result of two factors:

Finding:  the periphery is very important

[Question:  Can you explain all of these through demographics, rather than by structure?]

Preferential attachment:  key paradox against high clustering.

What about the rest of the industry?

As next step, (after seeing the emergence of the network), what difference does the small world have on the output?

[A long and involved discussion happened about the comparison with "random"]

Measures

Outcomes:

Summary: